Educational Measurement for Applied Researchers

1. What Is Measurement?
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

2. Construct, Framework and Test Development—From IRT Perspectives
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

3. Test Design
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

4. Test Administration and Data Preparation
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

5. Classical Test Theory
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

6. An Ideal Measurement
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

7. Rasch Model (The Dichotomous Case)
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

8. Residual-Based Fit Statistics
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

9. Partial Credit Model
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

10. Two-Parameter IRT Models
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

11. Differential Item Function
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

12. Equating
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

13. Facets Models
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

14. Bayesian IRT Models (MML Estimation)
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

15. Multidimensional IRT Models
Margaret Wu, Hak Ping Tam, Tsung-Hau Jen

Avainsanat: Statistics, Statistical Theory and Methods, Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law, Assessment, Testing and Evaluation, Mathematics in the Humanities and Social Sciences, Mathematical Software